Update app.py

app.py

@@ -7,23 +7,25 @@ import sqlite3
 import google.generativeai as genai
 import streamlit as st
 from PIL import Image
+import requests
+from io import BytesIO
 
 # Database setup
-conn = sqlite3.connect('chat_history.db')  
+conn = sqlite3.connect('chat_history.db') 
 c = conn.cursor()
 
 c.execute('''
-          CREATE TABLE IF NOT EXISTS history  
-          (role TEXT, message TEXT)
-          ''')
+         CREATE TABLE IF NOT EXISTS history 
+         (role TEXT, message TEXT)
+         ''')
 
 # Generative AI setup
-api_key = "AIzaSyC70u1sN87IkoxOoIj4XCAPw97ae2LZwNM"   
+api_key = "AIzaSyC70u1sN87IkoxOoIj4XCAPw97ae2LZwNM"  
 genai.configure(api_key=api_key)
 
 generation_config = {
-  "temperature": 0.9,
-  "max_output_tokens": 3000  
+ "temperature": 0.9,
+ "max_output_tokens": 3000 
 }
 
 safety_settings = []
@@ -35,74 +37,77 @@ st.set_page_config(page_title="Chatbot", page_icon="🤖")
 st.markdown("""
 <style>
 .container {
-    display: flex;
+   display: flex;
 }
 .logo-text {
-    font-weight:700 !important;
-    font-size:50px !important;
-    color: #f9a01b !important;
-    padding-top: 75px !important;
+   font-weight:700 !important;
+   font-size:50px !important;
+   color: #f9a01b !important;
+   padding-top: 75px !important;
 }
 .logo-img {
-    float:right;
+   float:right;
 }
 </style>
 <div class="container">
-    <p class="logo-text">Chatbot</p>
-    <img class="logo-img" src="https://media.roboflow.com/spaces/gemini-icon.png" width=120 height=120>
+   <p class="logo-text">Chatbot</p>
+   <img class="logo-img" src="https://media.roboflow.com/spaces/gemini-icon.png" width=120 height=120>
 </div>
 """, unsafe_allow_html=True)
 
 # Sidebar
 st.sidebar.title("Parameters")
 temperature = st.sidebar.slider(
-    "Temperature",
-    min_value=0.0,
-    max_value=1.0,
-    value=0.9,
-    step=0.01,
-    help="Temperature controls the degree of randomness in token selection. Lower temperatures are good for prompts that expect a true or correct response, while higher temperatures can lead to more diverse or unexpected results."
+   "Temperature",
+   min_value=0.0,
+   max_value=1.0,
+   value=0.9,
+   step=0.01,
+   help="Temperature controls the degree of randomness in token selection. Lower temperatures are good for prompts that expect a true or correct response, while higher temperatures can lead to more diverse or unexpected results."
 )
 max_output_tokens = st.sidebar.slider(
-    "Token limit",
-    min_value=1,
-    max_value=2048,
-    value=3000,
-    step=1,
-    help="Token limit determines the maximum amount of text output from one prompt. A token is approximately four characters. The default value is 2048."
+   "Token limit",
+   min_value=1,
+   max_value=2048,
+   value=3000,
+   step=1,
+   help="Token limit determines the maximum amount of text output from one prompt. A token is approximately four characters. The default value is 2048."
 )
 st.sidebar.title("Model")
 model_name = st.sidebar.selectbox(
-    "Select a model",
-    options=["gemini-pro", "gemini-pro-vision"],
-    index=0,
-    help="Gemini Pro is a text-only model that can generate natural language responses based on the chat history. Gemini Pro Vision is a multimodal model that can generate natural language responses based on the chat history and the uploaded images."
+   "Select a model",
+   options=["gemini-pro", "gemini-pro-vision"],
+   index=0,
+   help="Gemini Pro is a text-only model that can generate natural language responses based on the chat history. Gemini Pro Vision is a multimodal model that can generate natural language responses based on the chat history and the uploaded images."
 )
 
+# Initialize user_input in session state
+st.session_state["user_input"] = ""
+
 # Chat history
 st.title("Chatbot")
 chat_history = st.session_state.get("chat_history", []) 
 
 if len(chat_history) % 2 == 0:
-    role = "user"
+   role = "user"
 else:
-    role = "model"
+   role = "model"
 
 for message in chat_history:
-    r, t = message["role"], message["parts"][0]["text"]
-    st.markdown(f"**{r.title()}:** {t}")
-    
+   r, t = message["role"], message["parts"][0]["text"]
+   st.markdown(f"**{r.title()}:** {t}")
+   
 # User input
-user_input = st.text_area("", height=5, key="user_input")  
+user_input = st.text_area("", height=5, key="user_input") 
 
 # File uploader
 uploaded_files = st.file_uploader("Upload images here or paste screenshots", type=["png", "jpg", "jpeg"], accept_multiple_files=True, key="uploaded_files")
 
 # If files are uploaded, open and display them
 if uploaded_files:
-    for uploaded_file in uploaded_files:
-        image = Image.open(uploaded_file)
-        st.image(image)
+   for uploaded_file in uploaded_files:
+       image = Image.open(uploaded_file)
+       st.image(image)
 
 # Run button
 run_button = st.button("Run", key="run_button")
@@ -120,81 +125,62 @@ progress_bar = st.progress(0)
 st.markdown("""
 <style>
 .footer {
-    position: fixed;
-    left: 0;
-    bottom: 0;
-    width: 100%;
-    background-color: #f9a01b;
-    color: white;
-    text-align: center;
+   position: fixed;
+   left: 0;
+   bottom: 0;
+   width: 100%;
+   background-color: #f9a01b;
+   color: white;
+   text-align: center;
 }
 </style>
 <div class="footer">
-    <p>Made with Streamlit and Google Generative AI</p>
+   <p>Made with Streamlit and Google Generative AI</p>
 </div>
 """, unsafe_allow_html=True)
 
+# Clear chat history and image uploader
+if clear_button:
+   chat_history.clear()
+   st.session_state["chat_history"] = chat_history
+   st.session_state["user_input"] = ""
+   st.session_state["uploaded_files"] = None
+   st.experimental_rerun()
+
 # Save chat history to a text file
 if download_button:
-    chat_text = "\n".join([f"{r.title()}: {t}" for r, t in chat_history])
-    st.download_button(
-        label="Download chat history",
-        data=chat_text,
-        file_name="chat_history.txt",
-        mime="text/plain"
-    )
-
-# Generate model response
-if run_button or user_input:
-    if user_input:
-        chat_history.append({"role": role, "parts": [{"text": user_input}]}) 
-        st.session_state["user_input"] = ""
-        if role == "user":
-            
-            # Model code
-            model = genai.GenerativeModel(
-                model_name=model_name,   
-                generation_config=generation_config,
-                safety_settings=safety_settings
-            )
-            
-            if uploaded_files:
-                # Preprocess the uploaded files and convert them to image_parts
-                image_parts = []
-                for uploaded_file in uploaded_files:
-                    image = Image.open(uploaded_file).convert('RGB')
-                    image_parts.append({
-                        "mime_type": uploaded_file.type,
-                        "data": uploaded_file.read() 
-                    })
-                    # Display the uploaded images
-                    st.image(image)
-
-                # Add the user input to the prompt_parts
-                prompt_parts = [
-                    user_input,
-                ] + image_parts
-
-                # Use gemini-pro-vision model to generate the response
-                response = model.generate_content(prompt_parts, stream=True) 
-            else:
-                # Use gemini-pro model to generate the response
-                response = model.generate_content(chat_history, stream=True) 
-            
-            # Streaming effect
-            chat_history.append({"role": "model", "parts": [{"text": ""}]})
-            progress_bar.progress(0)
-            for chunk in response:
-                for i in range(0, len(chunk.text), 10):
-                    section = chunk.text[i:i + 10]
-                    chat_history[-1]["parts"][0]["text"] += section
-                    progress = min((i + 10) / len(chunk.text), 1.0)
-                    progress_bar.progress(progress)
-                    time.sleep(0.01)
-                    st.experimental_rerun()
-            progress_bar.progress(1.0)
-            
-            st.session_state["chat_history"] = chat_history
-            st.session_state["uploaded_files"] = None
-            
-    st.experimental_rerun()
+   chat_text = "\n".join([f"{r.title()}: {t}" for r, t in chat_history])
+   st.download_button(
+       label="Download chat history",
+       data=chat_text,
+       file_name="chat_history.txt",
+       mime="text/plain"
+   )
+
+ # Generate model response
+  if model_name == "gemini-pro":
+      response = genai.generate(
+          prompt=user_input,
+          temperature=temperature,
+          max_output_tokens=max_output_tokens
+      )
+  elif model_name == "gemini-pro-vision":
+      response = genai.generate(
+          prompt=user_input,
+          temperature=temperature,
+          max_output_tokens=max_output_tokens,
+          images=uploaded_files
+      )
+
+  # Update chat history
+  chat_history.append({"role": "model", "parts": [{"text": response}]})
+  st.session_state["chat_history"] = chat_history
+
+  # Update progress bar
+  progress_bar.progress(1)
+
+  # Clear user input
+  st.session_state["user_input"] = ""
+
+  # Rerun the app
+  st.experimental_rerun()